Identification of CDC25C as a Potential Biomarker in Hepatocellular Carcinoma Using Bioinformatics Analysis

Exploring the mechanism of genistein in treating hepatocellular carcinoma through network pharmacology and molecular docking

Objectives

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, with treatment options limited and outcomes often poor, especially in advanced stages. This study explores the therapeutic potential of genistein, a soybean-derived isoflavone, on HCC using network pharmacology to uncover its multi-targeted anti-cancer mechanisms.

Methods

Potential targets of genistein were predicted using databases such as Super-PRED, PharmMapper, and SwissTargetPrediction. Abnormally expressed genes in HCC tissues were analyzed from TCGA and GEO datasets, with genes linked to the prognosis of HCC patients selected as potential therapeutic targets. GO and KEGG pathway enrichment analyses were conducted for both genistein’s targets and the HCC-related gene set. Key targets were identified through network analysis using Cytoscape software. Molecular docking was performed with Autodock to assess the binding affinity between genistein and these key targets. The therapeutic effects of genistein on HCC were validated through animal experiments and cell line studies.

Results

This study identified 343 potential targets for genistein in treating hepatocellular carcinoma (HCC). Analyses revealed enrichment in cell cycle regulation pathways through GO and KEGG assessments. Transcriptomic data from HCC datasets unveiled 184 potential therapeutic targets, emphasizing cell cycle regulation. Notably, 12 proteins were identified as targets of both genistein and HCC treatment. Molecular docking studies demonstrated genistein’s strong binding affinity with CDC25C and MELK. In vitro and in vivo validations affirmed genistein’s role in inhibiting HCC proliferation by inducing G2/M phase arrest. This study elucidates genistein’s multi-target mechanism in suppressing HCC cell proliferation, supporting its potential clinical application in HCC treatment.

Conclusions

This study demonstrates that genistein effectively suppresses the malignant growth of HCC by interfering with the transition from the G2 to M phase, revealing a multifaceted mechanism of action.

SPRTN is involved in hepatocellular carcinoma development through the ER stress response

Endoplasmic reticulum (ER) stress, prompted by the accumulation of misfolded or unfolded proteins, triggers the activation of the unfolded protein response (UPR) pathway to restore ER homeostasis. This stress response is implicated in the development of hepatocellular carcinoma (HCC). A biallelic mutation in SPRTN is currently the only known single-gene mutation implicated in the early onset of HCC. However, the exact mechanism linking SPRTN mutations to HCC remains unclear. In our study, we analyzed SPRTN and UPR in 21 human HCC tissue samples using RT-qPCR, immunoblot, and immunohistochemistry. We found alterations in the expression levels of SPRTN and UPR-related genes and proteins in HCC samples. The impact of SPRTN on the ER stress response was assessed in SPRTN-depleted HepG2 cells through RNA sequencing, pull-down assay, comet assay, and mitotic index calculation. We demonstrated that SPRTN interacts with the UPR sensor GRP78. Furthermore, we observed a decrease in SPRTN levels during ER stress, and increased sensitivity to ER stress in SPRTN-depleted cells. These findings suggest an essential role for SPRTN in the ER stress response and provide new insights into HCC pathogenesis. This newly discovered function of SPRTN could significantly enhance our understanding and treatment of HCC.

Comprehensive Analysis Identifies Hyaluronan Mediated Motility Receptor and Cell Division Cycle 25C as Potential Prognostic Biomarkers in Head and Neck Squamous Cell Carcinoma

INTRODUCTION

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide, but its pathogenic mechanisms remain unclear. This study aimed to identify the potential biomarkers underlying the diagnosis and treatment of HNSCC.

METHODS

Weighted gene co-expression network analysis (WGCNA) followed by pathway enrichment analysis, analysis of infiltrating immune cells, survival analysis, and methylation analysis were applied to identify the potential hub genes underlying the prognosis of HNSCC. The expression of hub genes was validated by immunofluorescence staining.

RESULTS

A total of 10,274 differentially expressed genes (DEGs) were identified. Through WGCNA, the yellow module (R2 = 0.33, P = 2e-14) was confirmed to be the most significantly associated with the histological grade of HNSCC, and the "Cell Cycle" proved to be the most enriched signaling pathway. Based on the results of survival analysis and immune cell infiltration, 10 hub genes (HMMR, CENPK, AURKA, CDC25C, FEN1, CKS1B, MAJIN, PCLAF, SPC25, and STAG3) were identified. Eight of these (excluding MAJIN and STAG3) were confirmed by performing survival analysis using another dataset (GSE41613). Further, we identified 4 methylation loci in 3 hub genes (cg15122828 and cg20554926 in HMMR, cg12519992 in CDC25C, and cg2655739 in KIAA0101/PCLAF) as being significantly related to survival. Finally, we demonstrated the high mRNA and protein expression of HMMR and CDC25C in HNSCC patients.

CONCLUSION

Two real hub genes (HMMR and CDC25C) and 3 methylation loci were identified that could potentially serve as prognostic and therapeutic targets for HNSCC, which is significant for studying the pathological mechanisms underlying HNSCC and for developing novel therapies for this disease.

A dataset resource for clinically associated phosphosites in hepatocellular carcinoma

Phosphorylation is one of the most common post-translational modifications (PTMs) and is closely related to protein activity and function, playing a critical role during cancer development. Quantitative phosphoproteomic strategies have been widely used to study the underlying mechanisms of cancer progression or drug resistance. In this report, we analyzed the association of phosphosite levels originated from our previously reported proteogenomic study in hepatocellular carcinoma (HCC) with clinical parameters, including prognosis, recurrence, and Tumor-Node-Metastasis (TNM) stages. By using both the log-rank test and univariate Cox proportional hazards regression analysis, we found that the abundance levels of 1712 phosphosites were associated with prognosis and those of 393 phosphosites associated with recurrence. Besides, 692 phosphosites had different abundance levels among TNM stages (I, II, III+IV) by Analysis of Variance (ANOVA) test. Gene ontology (GO) biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using proteins with these statistically significant phosphosites. In conclusion, we provided a dataset resource for clinically associated phosphosites in HCC, which may be beneficial to liver cancer related basic research.

CDC25C Protein Expression Correlates with Tumor Differentiation and Clinical Outcomes in Lung Adenocarcinoma

Given that, even after multimodal therapy, early-stage lung cancer (LC) often recurs, novel prognostic markers to help guide therapy are highly desired. The mRNA levels of cell division cycle 25C (CDC25C), a phosphatase that regulates G2/M cell cycle transition in malignant cells, correlate with poor clinical outcomes in lung adenocarcinoma (LUAD). However, whether CDC25C protein detected by immunohistochemistry can serve as a prognostic marker in LUAD is yet unknown. We stained an LC tissue array and a cohort of 61 LUAD tissue sections for CDC25C and searched for correlations between CDC25C staining score and the pathological characteristics of the tumors and the patients' clinical outcomes. Clinical data were retrieved from our prospectively maintained departmental database. We found that high expression of CDC25C was predominant among poorly differentiated LUAD (p < 0.001) and in LUAD > 1cm (p < 0.05). Further, high expression of CDC25C was associated with reduced disease-free survival (p = 0.03, median follow-up of 39 months) and with a trend for reduced overall survival (p = 0.08). Therefore, high expression of CDC25C protein in LUAD is associated with aggressive histological features and with poor outcomes. Larger studies are required to further validate CDC25C as a prognostic marker in LUAD.

Comprehensive analysis of protein phosphatase 1 regulatory inhibitor subunit 14B, a molecule related to tumorigenesis, poor prognosis, and immune cell infiltration in lung adenocarcinoma

OBJECTIVE

To explore the relationship between Protein Phosphatase 1 Regulatory Inhibitor Subunit 14B (PPP1R14B) and the occurrence of lung adenocarcinoma (LUAD).

METHOD

PPP1R14B expression was investigated using various databases, and its molecular functions and pathways were evaluated using Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA). Then, the correlation between tumor mutations and PPP1R14B expression was analyzed. Furthermore, the regulation network and expression pathway axes of PPP1R14B were constructed. The correlation analysis between PPP1R14B and immune cell infiltration was performed using deconvolution algorithm analysis and the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemical (IHC) staining of the clinical samples were used for expression validation.

RESULTS

PPP1R14B showed high expression in tumor tissue. PPP1R14B was associated with T and N stages and poor prognosis and was linked to the cell cycle, DNA repair, and low immune response. High PPP1R14B expression was associated with high tumor mutation rates. The upstream and downstream genes of PPP1R14B were identified, along with the construction of a protein-protein interaction network (PPI network) and the expression pathway axes of PPP1R14B. PPP1R14B expression was associated with poor immune cell infiltration and a negative correlation between PPP1R14B and mast cell and eosinophil infiltration.

CONCLUSION

This study reveals high PPP1R14B expression in LUAD, its contribution to poor prognosis, molecular function, biological pathways, and impact on immune cell infiltration, and provides great insight into the role of PPP1R14B in LUAD tumorigenesis.

CDC25C is a prognostic biomarker and correlated with mitochondrial homeostasis in pancreatic adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is a common digestive tract malignant tumor with an extremely poor prognosis. The survival and prognosis may significantly improve if it is diagnosed early. Therefore, identifying biomarkers for early diagnosis is still considered a great clinical challenge in PAAD. Cell Division Cycle 25C (CDC25C), a cardinal cell cycle regulatory protein, directly mediates the G2/M phase and is intimately implicated in tumor development. In the current study, we aim to explore the possible functions of CDC25C and determine the potential role of CDC25C in the early diagnosis and prognosis of PAAD. Expression analysis indicated that CDC25C was overexpressed in PAAD . In addition, survival analysis revealed a strong correlation between the enhanced expression of CDC25C and poor survival in PAAD. Furthermore, pathway analysis showed that CDC25C is related to TP53 signaling pathways, glutathione metabolism, and glycolysis. Mechanically, our in vitro experiments verified that CDC25C was capable of promoting cell viability and proliferation. CDC25C inhibition increases the accumulation of ROS, inhibits mitochondrial respiration, suppresses glycolysis metabolism and reduces GSH levels. To summarize, CDC25C may be involved in energy metabolism by maintaining mitochondrial homeostasis. Our results suggested that CDC25C is a potential biological marker and promising therapeutic target of PAAD.

Construction of a Redox-Related Prognostic Model with Predictive Value in Survival and Therapeutic Response for Patients with Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) represents the most common histological subtype of lung cancer. Redox plays a significant role in oncogenesis and antitumor immunity. In this study, we aimed to investigate the prognostic redox-associated genes and construct a redox-based prognostic signature for LUAD.

Materials and Methods

A discovery cohort containing 479 LUAD samples from The Cancer Genome Atlas (TCGA) was analyzed. We identified prognostic redox-associated genes by weighted correlation network analysis (WGCNA) and univariate Cox regression analysis to construct a prognostic model via least absolute shrinkage and selection operator (LASSO)-multivariate Cox regression analyses. The performance of the redox-based model was validated in the TCGA cohort and an independent cohort of 456 samples by Cox regression analyses, log-rank test, and receiver operating characteristic (ROC) curves. Correlations of the model with clinicopathological variables and lymphocyte infiltration were assessed. Gene set enrichment analysis (GSEA) was used to clarify the underlying mechanism of the prognostic model. We constructed a nomogram based on the model and created calibration curves to show the accordance between actual survival and predicted survival of the nomogram.

Results

Stepwise analyses identified 6 prognostic redox-associated genes of LUAD and constructed a prognostic model that performed well in both the discovery and validation cohorts. The model was found to be associated with tumor stage, mutation of TP53 and EGFR, and lymphocyte infiltration. The model was mainly involved in the regulation of the cell cycle, DNA replication and repair, NADH metabolism, and the p53 signaling pathway. Calibration curves showed the high predictive accuracy of the nomogram.

Conclusions

This study explored the role of redox-associated genes in LUAD and constructed a prognostic model of LUAD. The signature was also associated with tumor progression and therapeutic response to immunotherapy. These findings contributed to uncovering the underlying mechanism and discovering novel prognostic predictor of LUAD.